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Proceedings Paper

Automatic SRAF printing detection based on contour extraction
Author(s): Liang Cao; Jie Zhang; Wenchao Jiang; Jiechang Hou; Dongqing Zhang; Wei-long Wang
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Paper Abstract

Sub-Resolution Assist Feature (SRAF) printing detection is critical during SRAF model building. Currently, SRAF printing detection on silicon wafer is mainly through human judgement on CDSEM images, which is inefficient and error prone. Therefore, a robust automatic SRAF printing classification mechanism is essential to improve detection accuracy and efficiency. This paper presents a method of classifying SRAF printing based on a database-independent contour extraction algorithm. By size calculation on extracted contour SRAF feature printing classification can be made automatically. This flow has been demonstrated to be able to correctly classify SRAF printing with consistent performance thus avoid the subjectivity and inconsistency in human judgement.

Paper Details

Date Published: 16 October 2017
PDF: 9 pages
Proc. SPIE 10451, Photomask Technology 2017, 104511J (16 October 2017); doi: 10.1117/12.2280186
Show Author Affiliations
Liang Cao, GLOBALFOUNDRIES Inc. (United States)
Jie Zhang, GLOBALFOUNDRIES Inc. (United States)
Wenchao Jiang, GLOBALFOUNDRIES Inc. (United States)
Jiechang Hou, GLOBALFOUNDRIES Inc. (United States)
Dongqing Zhang, GLOBALFOUNDRIES Inc. (United States)
Wei-long Wang, GLOBALFOUNDRIES Inc. (United States)

Published in SPIE Proceedings Vol. 10451:
Photomask Technology 2017
Peter D. Buck; Emily E. Gallagher, Editor(s)

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